Traditional QTL Mapping Research Articles

Haplotype-resolved genome and mapping of freezing tolerance in the wild potato Solanum commersonii.

Solanum commersonii (2n = 2x = 24, 1EBN, Endosperm Balance Number), native to the southern regions of Brazil, Uruguay, and northeastern Argentina, is the first wild potato germplasm collected by botanists and exhibits a remarkable array of traits related to disease resistance and stress tolerance. In this study, we present a high-quality haplotype-resolved genome of S. commersonii. The two identified haplotypes demonstrate chromosome sizes of 706.48 and 711.55Mb, respectively, with corresponding chromosome anchoring rates of 94.2 and 96.9%. Additionally, the contig N50 lengths are documented at 50.87 and 45.16Mb. The gene annotation outcomes indicate that the haplotypes encompasses a gene count of 39 799 and 40 078, respectively. The genome contiguity, completeness, and accuracy assessments collectively indicate that the current assembly has produced a high-quality genome of S. commersonii. Evolutionary analysis revealed significant positive selection acting on certain disease resistance genes, stress response genes, and environmentally adaptive genes during the evolutionary process of S. commersonii. These genes may be related to the formation of diverse and superior germplasm resources in the wild potato species S. commersonii. Furthermore, we utilized a hybrid population of S. commersonii and S. verrucosum to conduct the mapping of potato freezing tolerance genes. By combining BSA-seq analysis with traditional QTL mapping, we successfully mapped the potato freezing tolerance genes to a specific region on Chr07, spanning 1.25Mb, with a phenotypic contribution rate of 18.81%. In short, current research provides a haplotype-resolved reference genome of the diploid wild potato species S. commersonii and establishes a foundation for further cloning and unraveling the mechanisms underlying cold tolerance in potatoes.

Fine-mapping and candidate gene analysis of tuber eye depth in potato

Eye depth is an important agronomic trait affecting tubers' appearance, quality, and processing suitability. Hence, cultivating varieties with uniform shapes and shallow eye depth are important goals for potato breeding. In this study, based on the primary mapping of the tuber eye-depth locus using a small primary-segregating population, a large secondary-segregating population with 2,100 individuals was used to map the eye-depth locus further. A major quantitative trait locus for eye-depth on chromosome 10 was identified (designated qEyd10.1) using BSA-seq and traditional QTL mapping method. The qEyd10.1 could explain 55.0% of the eye depth phenotypic variation and was further narrowed to a 309.10 kb interval using recombinant analysis. To predict candidate genes, tissue sectioning and RNA-seq of the specific tuber tissues were performed. Genes encoding members of the peroxidase superfamily with likely roles in indole acetic acid regulation were considered the most promising candidates. These results will facilitate marker-assisted selection for the shallow-eye trait in potato breeding and provide a solid basis for eye-depth gene cloning and the analysis of tuber eye-depth regulatory mechanisms.

Application of bulk segregant RNA-Seq (BSR-Seq) and allele-specific primers to study soybean powdery mildew resistance

BackgroundPowdery mildew (PM) is one of the important soybean diseases, and host resistance could practically contribute to soybean PM management. To date, only the Rmd locus on chromosome (Chr) 16 was identified through traditional QTL mapping and GWAS, and it remains unclear if the bulk segregant RNA-Seq (BSR-Seq) methodology is feasible to explore additional PM resistance that might exist in other varieties.ResultsBSR-Seq was applied to contrast genotypes and gene expressions between the resistant bulk (R bulk) and the susceptible bulk (S bulk), as well as the parents. The ∆(SNP-index) and G’ value identified several QTL and significant SNPs/Indels on Chr06, Chr15, and Chr16. Differentially expressed genes (DEGs) located within these QTL were identified using HISAT2 and Kallisto, and allele-specific primers (AS-primers) were designed to validate the accuracy of phenotypic prediction. While the AS-primers on Chr06 or Chr15 cannot distinguish the resistant and susceptible phenotypes, AS-primers on Chr16 exhibited 82% accuracy prediction with an additive effect, similar to the SSR marker Satt431.ConclusionsEvaluation of additional AS-primers in the linkage disequilibrium (LD) block on Chr16 further confirmed the resistant locus, derived from the resistant parental variety ‘Kaohsiung 11’ (‘KS11’), not only overlaps with the Rmd locus with unique up-regulated LRR genes (Glyma.16G213700 and Glyma.16G215100), but also harbors a down-regulated MLO gene (Glyma.16G145600). Accordingly, this study exemplified the feasibility of BSR-Seq in studying biotrophic disease resistance in soybean, and showed the genetic makeup of soybean variety ‘KS11’ comprising the Rmd locus and one MLO gene.

Genome-Wide SNP Markers Accelerate Perennial Forest Tree Breeding Rate for Disease Resistance through Marker-Assisted and Genome-Wide Selection.

The ecological and economic importance of forest trees is evident and their survival is necessary to provide the raw materials needed for wood and paper industries, to preserve the diversity of associated animal and plant species, to protect water and soil, and to regulate climate. Forest trees are threatened by anthropogenic factors and biotic and abiotic stresses. Various diseases, including those caused by fungal pathogens, are one of the main threats to forest trees that lead to their dieback. Genomics and transcriptomics studies using next-generation sequencing (NGS) methods can help reveal the architecture of resistance to various diseases and exploit natural genetic diversity to select elite genotypes with high resistance to diseases. In the last two decades, QTL mapping studies led to the identification of QTLs related to disease resistance traits and gene families and transcription factors involved in them, including NB-LRR, WRKY, bZIP and MYB. On the other hand, due to the limitation of recombination events in traditional QTL mapping in families derived from bi-parental crosses, genome-wide association studies (GWAS) that are based on linkage disequilibrium (LD) in unstructured populations overcame these limitations and were able to narrow down QTLs to single genes through genotyping of many individuals using high-throughput markers. Association and QTL mapping studies, by identifying markers closely linked to the target trait, are the prerequisite for marker-assisted selection (MAS) and reduce the breeding period in perennial forest trees. The genomic selection (GS) method uses the information on all markers across the whole genome, regardless of their significance for development of a predictive model for the performance of individuals in relation to a specific trait. GS studies also increase gain per unit of time and dramatically increase the speed of breeding programs. This review article is focused on the progress achieved in the field of dissecting forest tree disease resistance architecture through GWAS and QTL mapping studies. Finally, the merit of methods such as GS in accelerating forest tree breeding programs is also discussed.

Linkage disequilibrium mapping: A journey from traditional breeding to molecular breeding in crop plants

Germplasms are the reservoir of agronomically important traits traditionally maintained by various tribal communities over the year. Maintaining these germplasms generations after generations has little value unless exploited for the desired agronomic traits like biotic and abiotic stress, yield attributes and nutritional enrichment. Association mapping, otherwise called linkage disequilibrium mapping, is a molecular breeding approach for characterizing complex traits with agronomic importance in crop plants. It is a systematic method for identifying novel traits and is treated as an alternative tool to traditional QTL mapping approaches, which involves correlating molecular markers with the phenotypic trait in a diversified population. The map's resolution in association mapping is based on the candidate-gene approach or genome-wide association approach. Therefore, association mapping studies offer a great perspective on crop genetic improvement. Still, considerably large-scale research is required to determine the sensible implementation of association mapping analysis in most crop plants. Currently, there is considerable interest in using association mapping approaches in crop breeding programs, which can be achieved by advanced genomic technology and the development of statistical computer software packages. Here, the linkage disequilibrium approach and its usefulness in association mapping studies, including the steps associated with it are discussed. The current status and future challenges in complex trait dissection by utilizing the linkage disequilibrium mapping in crop plants are also discussed.

QTL Map of Early- and Late-Stage Perennial Regrowth in Zea diploperennis.

Numerous climate change threats will necessitate a shift toward more sustainable agricultural practices during the 21st century. Conversion of annual crops to perennials that are capable of regrowing over multiple yearly growth cycles could help to facilitate this transition. Perennials can capture greater amounts of carbon and access more water and soil nutrients compared to annuals. In principle it should be possible to identify genes that confer perenniality from wild relatives and transfer them into existing breeding lines to create novel perennial crops. Two major loci controlling perennial regrowth in the maize relative Zea diploperennis were previously mapped to chromosome 2 (reg1) and chromosome 7 (reg2). Here we extend this work by mapping perennial regrowth in segregating populations involving Z. diploperennis and the maize inbreds P39 and Hp301 using QTL-seq and traditional QTL mapping approaches. The results confirmed the existence of a major perennial regrowth QTL on chromosome 2 (reg1). Although we did not observe the reg2 QTL in these populations, we discovered a third QTL on chromosome 8 which we named regrowth3 (reg3). The reg3 locus exerts its strongest effect late in the regrowth cycle. Neither reg1 nor reg3 overlapped with tiller number QTL scored in the same population, suggesting specific roles in the perennial phenotype. Our data, along with prior work, indicate that perennial regrowth in maize is conferred by relatively few major QTL.

QRf8-1, a Novel QTL for the Fertility Restoration of Maize CMS-C Identified by QTL-seq.

C-type cytoplasmic male sterility (CMS-C), one of the three major CMS types in maize, has a promising application prospect in hybrid seed production. However, the complex genetic mechanism underlying the fertility restoration of CMS-C remains poorly understood. The maize inbred line A619 is one of the rare strong restorer lines carrying the restorer gene Rf4, but different fertility segregation ratios are found in several F2 populations derived from crosses between isocytoplasmic allonucleus CMS-C lines and A619. In the present study, the segregation ratios of fertile to sterile plants in the (CHuangzaosi × A619) F2 and BC1F1 populations (36.77:1 and 2.36:1, respectively) did not follow a typical monogenic model of inheritance, which suggested that some F2 and BC1F1 plants displayed restored fertility even without Rf4. To determine the hidden locus affecting fertility restoration, next-generation sequencing-based QTL-seq was performed with two specific extreme bulks consisting of 30 fertile and 30 sterile rf4rf4 individuals from the F2 population. A major QTL related to fertility restoration, designated qRf8-1, was detected on the long arm of chromosome 8 in A619. Subsequently, qRf8-1 was further validated and narrowed down to a 17.93-Mb genomic interval by insertion and deletion (InDel) and simple sequence repeat (SSR) marker-based traditional QTL mapping, explaining 12.59% (LOD = 25.06) of the phenotypic variation. Thus, using genetic analyses and molecular markers, we revealed another fertility restoration system acting in parallel with Rf4 in A619 that could rescue the male sterility of CHuangzaosi. This study not only expands the original fertility restoration system but also provides valuable insights into the complex genetic mechanisms underlying the fertility restoration of CMS-C.

A framework for gene mapping in wheat demonstrated using the Yr7 yellow rust resistance gene.

We used three approaches to map the yellow rust resistance gene Yr7 and identify associated SNPs in wheat. First, we used a traditional QTL mapping approach using a double haploid (DH) population and mapped Yr7 to a low-recombination region of chromosome 2B. To fine map the QTL, we then used an association mapping panel. Both populations were SNP array genotyped allowing alignment of QTL and genome-wide association scans based on common segregating SNPs. Analysis of the association panel spanning the QTL interval, narrowed the interval down to a single haplotype block. Finally, we used mapping-by-sequencing of resistant and susceptible DH bulks to identify a candidate gene in the interval showing high homology to a previously suggested Yr7 candidate and to populate the Yr7 interval with a higher density of polymorphisms. We highlight the power of combining mapping-by-sequencing, delivering a complete list of gene-based segregating polymorphisms in the interval with the high recombination, low LD precision of the association mapping panel. Our mapping-by-sequencing methodology is applicable to any trait and our results validate the approach in wheat, where with a near complete reference genome sequence, we are able to define a small interval containing the causative gene.

Identification and fine mapping of a major locus controlling branching in Brassica napus

A candidate branching-controlling gene for qDBA09 was identified after delimiting a Brassica napus recessive locus within a 270-kb interval on chromosome A09. Although branching is an important trait associated with the adaptation and yield potential of rapeseed (Brassica napus), the genetic mechanisms underlining branching in this crop remain poorly understood. In this study, we characterized a naturally occurring rapeseed mutant, db1, which showed an ultrahigh branching density phenotype. By combining bulked segregant analysis (BSA) and the Brassica 60K SNP BeadChip Array, we identified two major quantitative trait loci (QTLs), qDBA09 and qDBC06, which were subsequently confirmed using the traditional QTL-mapping approach. Analysis of 208 individuals from a BC1F3 population indicated that the qDBA09 locus is a single Mendelian factor and that the dense branching phenotype is controlled by a single recessive gene. Furthermore, QTL analysis confirmed that qDBA09 explained between 9.5 and 70.5% of the variation in branching-related traits. Using 7785 individuals from the BC1F3 population, we mapped qDBA09 to a DNA fragment of approximately 270kb in length that contained 27 predicted genes, three of which were identified as potentially involved in the control of the dense branching trait. Based on the reported function of these genes, together with sequence comparisons and co-segregation analysis, we identified a potential candidate gene for the qDBA09 locus. The present findings lay the foundations for further in-depth research on the branching mechanisms of B. napus.

Identification and genetic mapping for rht-DM, a dominant dwarfing gene in mutant semi-dwarf maize using QTL-seq approach.

Semi-dwarfism is an agronomically important trait in breeding for stable high yields and for resistance to damage by wind and rain (lodging resistance). Many QTLs and genes causing dwarf phenotype have been found in maize. However, because of the yield loss associated with these QTLs and genes, they have been difficult to use in breeding for dwarf stature in maize. Therefore, it is important to find the new dwarfing genes or materials without undesirable characters. The objectives of this study were: (1) to figure out the inheritance of semi-dwarfism in mutants; (2) mapping dwarfing gene or QTL. Maize inbred lines '18599' and 'DM173', which is the dwarf mutant derived from the maize inbred line '173' through 60Co-γ ray irradiation. F2 and BC1F1 population were used for genetic analysis. Whole genome resequencing-based technology (QTL-seq) were performed to map dwarfing gene and figured out the SNP markers in predicted region using dwarf bulk and tall bulk from F2 population. Based on the polymorphic SNP markers from QTL-seq, we were fine-mapping the dwarfing gene using F2 population. In F2 population, 398 were dwarf plants and 135 were tall plants. Results of χ2 tests indicated that the ratio of dwarf plants to tall plants was fitted to 3:1 ratio. Furthermore, the χ2 tests of BC1F1 population showed that the ratio was fitted to 1:1 ratio. Based on QTL-seq, the dwarfing gene was located at the region from 111.07 to 124.56Mb of chromosome 9, and we named it rht-DM. Using traditional QTL mapping with SNP markers, the rht-DM was narrowed down to 400kb region between SNP-21 and SNP-24. The two SNPs were located at 0.43 and 0.11cM. Segregation analysis of F2 and BC1F1 indicated that the dwarfing gene was likely a dominant gene. This dwarfing gene was located in the region between 115.02 and 115.42Mb on chromosome 9.

Genetic Analysis of Fusarium Head Blight Resistance in CIMMYT Bread Wheat Line C615 Using Traditional and Conditional QTL Mapping.

Fusarium head blight (FHB) is a destructive wheat disease present throughout the world, and host resistance is an effective and economical strategy used to control FHB. Lack of adequate resistance resource is still a main bottleneck for FHB genetics and wheat breeding research. The synthetic-derived bread wheat line C615, which does not carry the Fhb1 gene, is a promising source of FHB resistance for breeding. A population of 198 recombinant inbred lines (RILs) produced by crossing C615 with the susceptible cultivar Yangmai 13 was evaluated for FHB response using point and spray inoculations. As the disease phenotype is frequently complicated by other agronomic traits, we used both traditional and multivariate conditional QTL mapping approaches to investigate the genetic relationships (at the individual QTL level) between FHB resistance and plant height (PH), spike compactness (SC), and days to flowering (FD). A linkage map was constructed from 3,901 polymorphic SNP markers, which covered 2,549.2 cM. Traditional and conditional QTL mapping analyses found 13 and 22 QTL for FHB, respectively; 10 were identified by both methods. Among these 10, three QTL from C615 were detected in multiple years; these QTL were located on chromosomes 2AL, 2DS, and 2DL. Conditional QTL mapping analysis indicated that, at the QTL level, SC strongly influenced FHB in point inoculation; whereas PH and SC contributed more to FHB than did FD in spray inoculation. The three stable QTL (QFhbs-jaas.2AL, QFhbp-jaas.2DS, and QFhbp-jaas.2DL) for FHB were partly affected by or were independent of the three agronomic traits. The QTL detected in this study improve our understanding of the genetic relationships between FHB response and related traits at the QTL level and provide useful information for marker-assisted selection for the improvement of FHB resistance in breeding.

Deciphering the genomic architecture of the stickleback brain with a novel multilocus gene-mapping approach.

Quantitative traits important to organismal function and fitness, such as brain size, are presumably controlled by many small-effect loci. Deciphering the genetic architecture of such traits with traditional quantitative trait locus (QTL) mapping methods is challenging. Here, we investigated the genetic architecture of brain size (and the size of five different brain parts) in nine-spined sticklebacks (Pungitius pungitius) with the aid of novel multilocus QTL-mapping approaches based on a de-biased LASSO method. Apart from having more statistical power to detect QTL and reduced rate of false positives than conventional QTL-mapping approaches, the developed methods can handle large marker panels and provide estimates of genomic heritability. Single-locus analyses of an F2 interpopulation cross with 239 individuals and 15 198, fully informative single nucleotide polymorphisms (SNPs) uncovered 79 QTL associated with variation in stickleback brain size traits. Many of these loci were in strong linkage disequilibrium (LD) with each other, and consequently, a multilocus mapping of individual SNPs, accounting for LD structure in the data, recovered only four significant QTL. However, a multilocus mapping of SNPs grouped by linkage group (LG) identified 14 LGs (1-6 depending on the trait) that influence variation in brain traits. For instance, 17.6% of the variation in relative brain size was explainable by cumulative effects of SNPs distributed over six LGs, whereas 42% of the variation was accounted for by all 21 LGs. Hence, the results suggest that variation in stickleback brain traits is influenced by many small-effect loci. Apart from suggesting moderately heritable (h2 ≈0.15-0.42) multifactorial genetic architecture of brain traits, the results highlight the challenges in identifying the loci contributing to variation in quantitative traits. Nevertheless, the results demonstrate that the novel QTL-mapping approach developed here has distinctive advantages over the traditional QTL-mapping methods in analyses of dense marker panels.

A genome-scale integrated approach aids in genetic dissection of complex flowering time trait in chickpea.

A combinatorial approach of candidate gene-based association analysis and genome-wide association study (GWAS) integrated with QTL mapping, differential gene expression profiling and molecular haplotyping was deployed in the present study for quantitative dissection of complex flowering time trait in chickpea. Candidate gene-based association mapping in a flowering time association panel (92 diverse desi and kabuli accessions) was performed by employing the genotyping information of 5724 SNPs discovered from 82 known flowering chickpea gene orthologs of Arabidopsis and legumes as well as 832 gene-encoding transcripts that are differentially expressed during flower development in chickpea. GWAS using both genome-wide GBS- and candidate gene-based genotyping data of 30,129 SNPs in a structured population of 92 sequenced accessions (with 200-250 kb LD decay) detected eight maximum effect genomic SNP loci (genes) associated (34% combined PVE) with flowering time. Six flowering time-associated major genomic loci harbouring five robust QTLs mapped on a high-resolution intra-specific genetic linkage map were validated (11.6-27.3% PVE at 5.4-11.7 LOD) further by traditional QTL mapping. The flower-specific expression, including differential up- and down-regulation (>three folds) of eight flowering time-associated genes (including six genes validated by QTL mapping) especially in early flowering than late flowering contrasting chickpea accessions/mapping individuals during flower development was evident. The gene haplotype-based LD mapping discovered diverse novel natural allelic variants and haplotypes in eight genes with high trait association potential (41% combined PVE) for flowering time differentiation in cultivated and wild chickpea. Taken together, eight potential known/candidate flowering time-regulating genes [efl1 (early flowering 1), FLD (Flowering locus D), GI (GIGANTEA), Myb (Myeloblastosis), SFH3 (SEC14-like 3), bZIP (basic-leucine zipper), bHLH (basic helix-loop-helix) and SBP (SQUAMOSA promoter binding protein)], including novel markers, QTLs, alleles and haplotypes delineated by aforesaid genome-wide integrated approach have potential for marker-assisted genetic improvement and unravelling the domestication pattern of flowering time in chickpea.

Deploying QTL-seq for rapid delineation of a potential candidate gene underlying major trait-associated QTL in chickpea.

A rapid high-resolution genome-wide strategy for molecular mapping of major QTL(s)/gene(s) regulating important agronomic traits is vital for in-depth dissection of complex quantitative traits and genetic enhancement in chickpea. The present study for the first time employed a NGS-based whole-genome QTL-seq strategy to identify one major genomic region harbouring a robust 100-seed weight QTL using an intra-specific 221 chickpea mapping population (desi cv. ICC 7184 × desi cv. ICC 15061). The QTL-seq-derived major SW QTL (CaqSW1.1) was further validated by single-nucleotide polymorphism (SNP) and simple sequence repeat (SSR) marker-based traditional QTL mapping (47.6% R2 at higher LOD >19). This reflects the reliability and efficacy of QTL-seq as a strategy for rapid genome-wide scanning and fine mapping of major trait regulatory QTLs in chickpea. The use of QTL-seq and classical QTL mapping in combination narrowed down the 1.37 Mb (comprising 177 genes) major SW QTL (CaqSW1.1) region into a 35 kb genomic interval on desi chickpea chromosome 1 containing six genes. One coding SNP (G/A)-carrying constitutive photomorphogenic9 (COP9) signalosome complex subunit 8 (CSN8) gene of these exhibited seed-specific expression, including pronounced differential up-/down-regulation in low and high seed weight mapping parents and homozygous individuals during seed development. The coding SNP mined in this potential seed weight-governing candidate CSN8 gene was found to be present exclusively in all cultivated species/genotypes, but not in any wild species/genotypes of primary, secondary and tertiary gene pools. This indicates the effect of strong artificial and/or natural selection pressure on target SW locus during chickpea domestication. The proposed QTL-seq-driven integrated genome-wide strategy has potential to delineate major candidate gene(s) harbouring a robust trait regulatory QTL rapidly with optimal use of resources. This will further assist us to extrapolate the molecular mechanism underlying complex quantitative traits at a genome-wide scale leading to fast-paced marker-assisted genetic improvement in diverse crop plants, including chickpea.

Efficiency of haplotype-based methods to fine-map QTLs and embryonic lethal variants affecting fertility: Illustration with a deletion segregating in Nordic Red cattle

Despite its importance, fertility has been declining in many cattle populations. In dairy cattle, this decline is often attributed to the negative correlation between fertility and productions traits. Recent studies showed that embryonic lethal variants might also account for a non-negligible fraction of the fertility decline. Therefore identification of such embryonic lethal variants is essential to improve fertility. We herein illustrate, with an example of a large recessive lethal deletion recently identified in Nordic Red cattle, that haplotype-based method are particularly efficient to identify such embryonic lethal variants. We first show that haplotypes can be used in traditional QTL mapping approaches and that they present very high linkage disequilibrium with underlying variants. Haplotypes can also be used in scan for lack of homozygosity. Indeed, if a haplotype is associated to a recessive lethal variant, significantly fewer living individuals will be homozygote for that haplotype than expected. For both approaches, haplotype-based methods were particularly efficient. The lack of homozygosity approach achieved higher significance than the QTL approach. Only frequent variants can be detected with both approaches unless huge genotyped cohorts are available. An alternative approach would rely on identifying potential harmful variants in next-generation sequencing data followed by the genotyping of a larger population for these variants.

A Bayesian Partition Method for Detecting Pleiotropic and Epistatic eQTL Modules

Studies of the relationship between DNA variation and gene expression variation, often referred to as “expression quantitative trait loci (eQTL) mapping”, have been conducted in many species and resulted in many significant findings. Because of the large number of genes and genetic markers in such analyses, it is extremely challenging to discover how a small number of eQTLs interact with each other to affect mRNA expression levels for a set of co-regulated genes. We present a Bayesian method to facilitate the task, in which co-expressed genes mapped to a common set of markers are treated as a module characterized by latent indicator variables. A Markov chain Monte Carlo algorithm is designed to search simultaneously for the module genes and their linked markers. We show by simulations that this method is more powerful for detecting true eQTLs and their target genes than traditional QTL mapping methods. We applied the procedure to a data set consisting of gene expression and genotypes for 112 segregants of S. cerevisiae. Our method identified modules containing genes mapped to previously reported eQTL hot spots, and dissected these large eQTL hot spots into several modules corresponding to possibly different biological functions or primary and secondary responses to regulatory perturbations. In addition, we identified nine modules associated with pairs of eQTLs, of which two have been previously reported. We demonstrated that one of the novel modules containing many daughter-cell expressed genes is regulated by AMN1 and BPH1. In conclusion, the Bayesian partition method which simultaneously considers all traits and all markers is more powerful for detecting both pleiotropic and epistatic effects based on both simulated and empirical data.

Marker Imputation in Barley Association Studies

Association mapping requires high marker density, potentially leading to many missing marker data and to high genotyping costs. In human genetics, methods exist to impute missing marker data and whole markers typed in a reference panel but not in the experimental dataset. We sought to determine if an imputation method developed for human data would function effectively in a barley (Hordeum vulgare L.) panel. The panel contained 98 lines, 2517 single nucleotide polymorphism (SNP) markers, and 716 Diversity Arrays Technology (DArT) markers. Averaged over markers, masked scores were correctly imputed 97.1% of the time. We chose 610 and 273 tag markers in two‐ and six‐row barley subpopulations, respectively. Despite this low number of tags, imputation accuracy was such that for about 80% of non‐tag markers, the prediction r2 between imputed and true scores was 0.8 or higher. When DArT markers were used as tags, SNP markers were imputed with similar accuracy, suggesting that the method can convert association information from one marker system (e.g., DArT) to another marker system (e.g., SNP). We believe marker imputation methods will have an important future in association studies as a component of tagging methods and in reducing problems due to missing data.

Association mapping of yellow pigment in an elite collection of durum wheat cultivars and breeding lines

Association mapping (AM) is an alternative or complementary strategy to QTL mapping for describing associations between genotype and phenotype based on linkage disequilibrium (LD). Yellow pigment (YP), an important end-use quality trait in durum wheat (Triticum turgidum L. var. durum), was evaluated to determine the ability of AM to identify previously published QTL and to identify genomic regions for further genetic dissection. The YP concentration was determined for 93 durum wheat accessions sampled from a variety of geographic origins. Analysis of population structure using distance- and model-based estimates indicated the presence of five subpopulations. Using subpopulation assignments as covariates, significant (P < 0.05) marker-trait associations for YP were detected on all chromosomes of the durum genome. Using AM, genomic regions housing known YP QTL were confirmed, most notably the group 7 chromosomes. In addition, several markers on the group 1, 2, and 3 chromosomes were identified where QTL have yet to be reported. A phytoene synthase gene, Psy1-B1, a potential candidate gene for YP, was significantly associated with YP and was in strong LD with microsatellite markers on the distal end of 7BL. Our results demonstrated that AM complemented traditional QTL mapping techniques and identified novel QTL that should be the target of further genetic dissection.

Quantitative Trait Linkage Analysis Using Gaussian Copulas

Mapping and identifying variants that influence quantitative traits is an important problem for genetic studies. Traditional QTL mapping relies on a variance-components (VC) approach with the key assumption that the trait values in a family follow a multivariate normal distribution. Violation of this assumption can lead to inflated type I error, reduced power, and biased parameter estimates. To accommodate nonnormally distributed data, we developed and implemented a modified VC method, which we call the "copula VC method," that directly models the nonnormal distribution using Gaussian copulas. The copula VC method allows the analysis of continuous, discrete, and censored trait data, and the standard VC method is a special case when the data are distributed as multivariate normal. Through the use of link functions, the copula VC method can easily incorporate covariates. We use computer simulations to show that the proposed method yields unbiased parameter estimates, correct type I error rates, and improved power for testing linkage with a variety of nonnormal traits as compared with the standard VC and the regression-based methods.